Mixture Of Probabilistic Factor Analyzers For Market Risk Measurement: Empirical Evidence From The Tunisian Foreign Exchange Market
Open Access
- 4 May 2017
- journal article
- Published by Virtus Interpress in Risk Governance and Control: Financial Markets & Institutions
- Vol. 7 (2), 158-169
- https://doi.org/10.22495/rgcv7i2c1p4
Abstract
In this paper, we propose a new approach for Basel-Compliant Value-at-Risk (VaR) estimation in financial portfolio risk management, which combines Gaussian Mixture Models with probabilistic factor analysis models. This new mixed specification provides an alternative, compact, model to handle co-movements, heterogeneity and intra-frame correlations in financial data. This results in a model which concurrently performs clustering and dimensionality reduction, and can be considered as a reduced dimension mixture of probabilistic factor analyzers. For maximum likelihood estimation we have used an iterative approach based on the Alternating Expectation Conditional Maximization (AECM) algorithm. Using a set of historical data in a rolling time window, from the Tunisian foreign exchange market, the model structure as well as its parameters are determined and estimated. Then, the fitted model combined with a modified Monte-Carlo simulation algorithm was used to predict the VaR. Through a Backtesting analysis, we found that this new specification exhibits a good fit to the data compared to other competing approaches, improves the accuracy of VaR prediction, possesses more flexibility, and can avoid serious violations when a financial crisis occurs.Keywords
This publication has 17 references indexed in Scilit:
- Performance of Value at Risk models in the midst of the global financial crisis in selected CEE emerging capital marketsEconomic Research-Ekonomska Istraživanja, 2015
- Multifractality and value-at-risk forecasting of exchange ratesPhysica A: Statistical Mechanics and its Applications, 2014
- Exchange Rate Pass-Through in Developing and Emerging Markets: A Survey of Conceptual, Methodological and Policy Issues, and Selected Empirical FindingsThe Journal of Development Studies, 2013
- Developing a stress testing framework based on market risk modelsJournal of Banking & Finance, 2008
- The EM Algorithm and Extensions, 2EPublished by Wiley ,2008
- How Accurate Are Value‐at‐Risk Models at Commercial Banks?The Journal of Finance, 2002
- Finite Mixture ModelsWiley Series in Probability and Statistics, 2000
- Evaluating Interval ForecastsInternational Economic Review, 1998
- The EM Algorithm—an Old Folk-song Sung to a Fast New TuneJournal of the Royal Statistical Society Series B: Statistical Methodology, 1997
- Testing the null hypothesis of stationarity against the alternative of a unit root: How sure are we that economic time series have a unit root?Journal of Econometrics, 1992